Comparing network flow data in the mobile network is unpredictable while looking at nodes level and overall user end level. At node level quality of service cannot be predictable whereas overall quality of service after reaching end user it is stationary. In this project using energy maps to reduce energy consumption levels.
In this, we use path integration algorithm which will calculate nodes paths and share energy levels of each node with other nodes where each node will construct energy fields.
Strength planning and optimization constitute one of the enormous challenges for high-mobility networks. A novel framework to proportion, retain and refine quit- to-stop energy metrics inside the joint reminiscence of the nodes, over the years scales over which this records may be unfolded to the community and utilized for energy making plans decisions. We construct maps of stop-to-quit strength metrics that permit electricity optimization in excessive-mobility networks. We display the way to (1) compute the spatial derivatives of energy potentials in high-mobility networks, distribute, proportion, fuse, and refine energy maps through the years by way of records trade at some point of encounters, (2) permit the nodes to use strength maps for power planning and optimization in postpone- tolerant, excessive-mobility networks.
We outline the coherence time because the most length for which the cease-to-cease QoS metric remains kind of steady, and the spreading period because of the minimum length required to spread QoS records to all the nodes.
We show that if the coherence time is greater than the spreading length, the end-to-quit QoS metric can be tracked. We consciousness on the energy consumption as the stop-to-end QoS metric, and describe a unique approach by using which an electricity map can be constructed and subtle inside the joint reminiscence of the cellular nodes.
Download Reducing Node Energy Consumption Using Energy Maps Project code, Document.